TY - JOUR

T1 - Uncertainty propagation and sensitivity analysis in composite manufacturing cost estimation: ALPHA-framework and cost tool development

AU - Hueber, Christian

AU - Schwingshandl, Nikolaus

AU - Schledjewski, Ralf

PY - 2019/4/19

Y1 - 2019/4/19

N2 - The presented ALPHA cost tool is a novel highly flexible bottom-up parametric hybrid cost estimation framework. It combines the benefits of both methods with the aim of providing cost information during all product development phases. The software offers full transparency to the user and advanced two-level uncertainty management to not only understand any project’s cost structure but also aid to identify its cost driving parameters. The implementation of sensitivity analysis makes the intrinsic uncertainty inevitable embedded in cost estimation become graspable. Gaussian error propagation offers direct feedback without extra calculation time while classic Monte Carlo Simulation gives detailed insight through post estimation analysis. From the vast number of commercially available or self-developed cost tools many probably already incorporate uncertainty measures similar to those proposed here. But this article shows both the potential of the additionally obtainable information from uncertainty propagation and demonstrates a way of integrating these risk considerations into a self-developed cost tool.

AB - The presented ALPHA cost tool is a novel highly flexible bottom-up parametric hybrid cost estimation framework. It combines the benefits of both methods with the aim of providing cost information during all product development phases. The software offers full transparency to the user and advanced two-level uncertainty management to not only understand any project’s cost structure but also aid to identify its cost driving parameters. The implementation of sensitivity analysis makes the intrinsic uncertainty inevitable embedded in cost estimation become graspable. Gaussian error propagation offers direct feedback without extra calculation time while classic Monte Carlo Simulation gives detailed insight through post estimation analysis. From the vast number of commercially available or self-developed cost tools many probably already incorporate uncertainty measures similar to those proposed here. But this article shows both the potential of the additionally obtainable information from uncertainty propagation and demonstrates a way of integrating these risk considerations into a self-developed cost tool.

UR - http://www.scopus.com/inward/record.url?scp=85066504022&partnerID=8YFLogxK

U2 - 10.1080/20550340.2019.1599536

DO - 10.1080/20550340.2019.1599536

M3 - Article

VL - 5.2019

SP - 69

EP - 84

JO - Advanced Manufacturing: Polymer and Composites Science

JF - Advanced Manufacturing: Polymer and Composites Science

SN - 2055-0359

IS - 2

ER -